Many real-world tasks require fast planning of highly dynamic movements for their execution in real-time. The success often hinges on quickly finding one of the few plans that can achieve the task at all. A further challenge is to quickly find a plan which optimizes a desired cost. In this paper, we will discuss this problem in the context of catching small flying targets efficiently. This can be formulated as a non-linear optimization problem where the desired trajectory is encoded by an adequate parametric representation. The optimizer generates an energy-optimal trajectory by efficiently using the robot kinematic redundancy while taking into account maximal joint motion, collision avoidance and local minima. To enable the resulting method to work in real-time, examples of the global planner are generalized using nearest neighbour approaches, Support Vector Machines and Gaussian process regression, which are compared in this context. Evaluations indicate that the presented method is highly efficient in complex tasks such as ball-catching
On-orbit servicing involves a new class of space missions in which a servicer spacecraft is launched into the orbit of a target spacecraft, the client. The servicer navigates to the client with the intention of manipulating it, using a robotic arm. Within this framework, this work presents a new robotic experimental facility which was recently built at the DLR to support the development and experimental validation of such orbital servicing robots. The facility allows reproducing a closeproximity scenario under realistic three-dimensional orbital dynamics conditions. Its salient features are described here, to include a fully actuated macro-micro system with multiple sensing capabilities, and analyses on its performance including the amount of space environment volume that can be simulated.
The grasping and stabilization of a spinning, noncooperative target satellite by means of a free-flying robot is addressed. A method for computing feasible robot trajectories for grasping a target with known geometry in a useful time is presented, based on nonlinear optimization and a look-up table. An off-line computation provides a data base for a mapping between a four-dimensional input space, to characterize the target motion, and an N-dimensional output space, representing the family of time-parameterized optimal robot trajectories. Simulation results show the effectiveness of the data base for computing grasping maneuvers in a useful time, for a sample range of spinning motions. The debris object consists of a satellite with solar appendages in Low Earth Orbit, which presents collision avoidance and timing challenges for executing the task.
Space exploration and exploitation depend on the development of on-orbit robotic capabilities for tasks such as servicing of satellites, removing of orbital debris, or construction and maintenance of orbital assets. Manipulation and capture of objects on-orbit are key enablers for these capabilities. This survey addresses fundamental aspects of manipulation and capture, such as the dynamics of space manipulator systems (SMS), i.e., satellites equipped with manipulators, the contact dynamics between manipulator grippers/payloads and targets, and the methods for identifying properties of SMSs and their targets. Also, it presents recent work of sensing pose and system states, of motion planning for capturing a target, and of feedback control methods for SMS during motion or interaction tasks. Finally, the paper reviews major ground testing testbeds for capture operations, and several notable missions and technologies developed for capture of targets on-orbit.
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